How AI Will Change Business Forever w/ Salim Ismail | EP #46

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Visit phoenix.edu Some people think nature is like this, but actually it's like this. That's why Columbia engineers everything we make for anything nature can throw at you. Columbia engineered for whatever. We're living in a world that has been pummeled by exponential technologies.

The world is now turned into information.

The first time we started hearing about artificial intelligence was at a conference in Dartmouth in 1956.

The first article that came out saying that robots are going to take all the jobs in five years appeared in 1964.

AI is not going to take your job. It's someone using AI that's going to take your job.

The AI plus a human being that always turns out to be the best competitor.

It's a tsunami of change and you're either an exo surfing on top of the tsunami or you're being crushed by it.

Get started as fast as you can because this is one of those where you cannot afford to be left behind on this paradigm.

Welcome to Moonshots and Mindsets here with my dear friend Salim Ismael, the CEO of OpenExo and my co author on a new book called exponential organizations 2.0 Saleem. The world is so different than, than it's ever been. And for an entrepreneur, especially an exponential entrepreneur, you're either building an exponential organization or you're dead on arrival. I mean, I think it's that black and white, you know, it's going to be an exo or nothing in this decade ahead.

We used to say the world changed radically ten years ago, but the world changed radically like four months ago.

And so everything is different from then and it's accelerating. You know, when I'm on stage and people say, when is this going to slow down? When is the world going to like, you know, where's the on off switch? There is no on off switch. There's no velocity meter. It's accelerating. And we can talk about why it's accelerating. But in this session we're going to talk about one of the most important external attributes of being an exponential organization, which is AI and algorithms. But before we get there, for those just hearing this for the first time, Salim, what is an exponential organization?

An exponential organization is a 21st century organization, focused and delivering minimum 10x better, faster and cheaper than your more linear peers. The 20th century was all about building scalable organizations focused on efficiency and predictability. Today you need to be agile, flexible, adaptable and fast. And that's what an exos with a set of characteristics and AI and algorithms is one of those.

I like to say that we're living in a world that has been pummeled by exponential technologies. I liken it to the asteroid that impacted the planet 65 million years ago and it changed the world so rapidly, the environment so rapidly that the slow lumbering dinosaurs died and went extinct. And the furry little mammals our very proud ancestors evolved to dominate. And the asteroid that struck the world now over the last 20, 30 years and accelerating is all of these exponential technologies. Computation, sensors, networks, AI, robotics, 3D printing, synthetic biology, AR, VR, blockchain, all these technologies are just like transforming. It's a tsunami of change. You're either an exo surfing on top of the tsunami or you're being crushed by it. I think anybody who's not been asleep for the last six months knows that one of those tsunami causing attributes is AI and algorithms. Let's jump into that. It's a super exciting opportunity. I've mentioned this in one of our previous podcasts, but I saw a tweet from a friend of ours that said we're not far from the first three person billion dollar company starting literally overnight. And I think that's true.

Yeah, I think that's exactly right. And it goes back to your 6Ds premise, right where you're digitizing the world. The world is now turned into information. Our relationships are not digital, our memories aren't in our heads. And now with all of that tsunami of data, we actually need AI and algorithms to help manage and massage it all. And the business models that emerge for that are going to be really profound. So if we look at a quick definition, AI and algorithms are the use of artificial intelligence and algorithms to basically make sense of data sets and create value from those data sets, and then eventually in an exo, create a business model around them. Google is the quintessential example of this with the creation of AdSense and PageRank. The massive amount of value it's created from that is unbelievable. Now we're seeing that pervasively being applied across the board. The world, world runs on AI today.

Yeah, it does. And just to put AI in a frame, I think that people can appreciate is why now what has changed? Because there's something that's actually changed. In the last five years, we've met certain thresholds that's transformed the world. If you think about it, AI is over as a concept, is 60 plus years old. The first time we started hearing about artificial intelligence was at a conference in Dartmouth in 1956. And then people say, well, no, it's the deep learning models and deep learning concepts that are new, but that actually emerged in like 1960s, mid-60s. So why now? Why are we seeing this huge tsunami of change where every trillion dollar company is betting their future on these generative AI models? And it's four things. The first, as you well know, is computation. Right. We're in this massive growth of computation that's doubling every 18 to 24 months more is law, what Ray Kurzweil calls the law of accelerating returns, doubling power and power and power. And finally we've got enough computational power on the cloud. We have a new set of massive Nvidia computational chips that are being deployed and that's allowing us to run these deep learning models that were never possible at scale before.

Yeah, in the past we were focused on narrow AI, right, Fuzzy logic in your digital camera or anti lock breaking systems, or credit card fraud detection, very niche applications. Then we went to deep learning where you, you basically gave it and it learned as it went along. And that got us to a certain point. I remember chatting with Geoffrey Hinton a few years ago. I think it was like 2017, and he was speaking at a conference and I said, you know, where does deep learning go? And he said, we've hit the end of the life cycle. We need the next breakthrough to happen so that AI can progress to the next level. I don't know what that is. And literally at the same time the transformer PA was being published and that turns out to be the big thing that all these LLMs are based on.

The second major thing that's occurred is that we have a massive amount of data. So global data has been doubling roughly every two years. We're about to hit 175 zettabytes. I love that. Which is 175 billion megabytes of data. And this data is now labeled. It was an article recently that said we're going to create a new term called a yodabyte which is coming online. I love that.

You know, the stat that always blows my mind is that goes. The one that goes. In the last six months we created more data than the entire history of humanity did until that point. And then we just did in the last six months. And then we'll do it again in the next three months. And then you're like, okay, I Just can't. I would suggest that we can't comprehend or process that.

A quick break from our episode. On June 6, Salim and I are going to be running a free three hour workshop on how to actually build and design an exponential organization. Would love to have you join us. If you join us on June 6th, first of all, you'll get free access to the book Exponential Organizations 2.0. Access to an AI that we've built that allows you to query the book and helps you design your exponential organization. It's June 6th, it's three hours, it's free. We've never done this before. Click on the link below diamandis.com EXO and join us. All right, now back to the episode. So computation, massive amount of data, label data, which is really the food stock for the large language models. You know, OpenAI, stability, bard, all of these. The third thing that's happening that is really changing this universe is the cost to train AI systems has gone down by 99.5% in the last five years. So the efficiency of the algorithms. This is something that people don't realize. This is what's speeding up the world, ladies and gentlemen. It's the fact that the tech is getting so much better that every dollar goes so much further. So in genome sequencing, it cost Craig Venter $100 million to sequence one genome. Now it's 100 bucks. So $100 million will sequence, I mean $100 million will sequence a million genomes, not one genome in the same way. It used to be. Call it 1000 bucks to sequence, to actually train AI model. And now it's like 50 cents or 5 bucks. It's transformative how fast it's going. And then the third, my favorite phrase and half people listening are not going to know this. But no bucks, no Buck Rogers is the amount of massive capital. I have a reference number that in 2021, during the pandemic, $160 billion of global corporate investment went into AI alone. It's crazy.

And then Facebook pretty much doubled it on its own just in the trying to go after their different angles. I think that you add this together and this becomes one of the most important characteristics of an exponential organization. Because as you build out, you're looking at what data sources, what can I turn into information? And then you need algorithms to make sense of it all. And the comment that you made earlier about startups being created out of this are going to be profound. The two domains that blow my mind just specifically to LLMs are doctors and lawyers, right And I can like literally see the point where you literally don't need a doctor and you don't need a lawyer in a human form of any kind. Because the law. You can just tell ChatGPT to build a contract and write a contract for you.

Well, it can right now. Really well. Right. And in fact, a lot of people are using ChatGPT as their physician. Interesting reference point. Right. So ChatGPT goes live in November of 2022. In January, two months later, it passes the U.S. medical licensing exam, USMLE, which is insane. You normally need, you know, four years of medical school, two years of residency or internship to pass that. And it does that. And here's a good example of how it's going to massively disrupt. I think eventually two things are going to happen. Your AI will be your diagnostician. Zero question about that. Before then it's going to become malpractice to diagnose a patient without AI as your co pilot in the loop. Here's a data point. Do you have any idea how many medical journal articles are published every day? I may have shared this with you right now. 7,000, 7,000. 7,000 per day. So ask yourself, how many of those journals has my doctor read this morning?

Well, Daniel Kraft, the one he referenced to me was that there's 2,500 cancer research papers published a day. If you're an oncologist, there's no way you can keep track of all of that. You need an AI to just surf that tsunami of data and make sense of it all.

Yeah, we have at Fountain Life, where I'm proud to be executive chairman in an upload, we upload our members. They go through an upload every year and it's 150 gigabytes of data. It's their full genome, full body MRI, brain, brain vasculature, coronary CT, 80 blood biomarkers. And they're changing all the time. And the database that we look into of knowledge is changing all the time. And it's kind of pathetic to think about a poor human trying to make heads or tails of that information. Cannot. So it's changing fast.

You know, let's look at our brain, right? It's not had an upgrade in 50,000 years. It's stuck inside this. It's a liter and a half volume stuck inside here. And it's trapped. It has evolutionary incremental gains. And we are stuck with all these cognitive biases like sunk cost bias and framing bias and all these other biases that we can't get around very easily. These cognitive biases.

Yeah. So let's dive into that one second. And we'll come back to. To the more basic uses of AI and algorithms. I think one of the things we're all eventually going to have our own version of Jarvis. I don't think it's very far away. We have. I won't say her name, it's spelled A L, E X A. Sitting across the room here. She'll wake up. We have that and Siri and Google's variation. And I don't know if Cortana is still a thing or not, but they're early versions. And we're going to get to a point where we all have an AI that is on our bodies, literally in our bodies, and we give permission to read everything we write, listen to our conversations, read our emails, our text messages, everything, because then that AI is going to be able to be there to facilitate anything we want. And one of the things I wanted to facilitate is, hey, tell me when I have a cognitive bias. Because cognitive biases are. Unfortunately, we cannot process all the information that comes into our minds. We have a very little flow over evolutionary time period. Our brains evolved these cognitive biases. They were neural hacks to help you reach conclusions quicker. Like a familiarity bias, someone who looks like you, you trust more. Or recency bias, you give higher value to more recent information. Or a negativity bias. Right. Our damned amygdalas that are destroying the planet and the Crisis News Network is taking advantage of them, which you give far more value to negative news than positive news.

What was the stat you and Steven uncovered in abundance? Is it 10x?

Yeah. So, yeah, this is something that Steven Kotler and I found in looking at the news media. And you can do the experiment yourself, pick up a newspaper. I don't read them anymore, but if I'm at a conference someplace, I'll play the game and count the negative stories to positive stories. It's 10 to 1. And on cable News Network, whatever the case might be, you're getting 95% negative stories. Every murder brought to you over and over again in living color, streamed to 20 devices.

Yeah. This is such an important point. This was one of the most important pieces out of abundance that I can ever remember reading. Was this identification of this because we evolved that amygdala when we were running around on the plains of Africa. If you heard a noise in the bushes, you ran because bad news could kill you. Right. If I missed some good news, I might miss some fruit that I could eat. But if I missed a Piece of bad news, I died. So way more, we're way more optimized for listening to bad news than good news because of the survival factor. And when I noticed one thing that I noticed when we were teaching courses at Singularity University, when you showed somebody something new, they immediately, because of the unknown factor, they related to it as danger, right? So the first, when you saw somebody, the autonomous car, the first reaction is, oh my God, stop the car, because that car might kill somebody. And then we start with this negative perception of the technology and over a long period of time, we kind of evolve a better version of it, et cetera, et cetera. We're not evidentiary based at all in terms of how we cognit or analyze the world.

It's a problem that's screwing with the world, right? Our core politics, our core software is fear and scarcity versus abundance and optimism. Fear and scarcity puts you back on your heels in a protective world versus abundance and optimism. Against a mindset shift where you're taking advantage and you're jumping on, how can I use that? Where can I go with it? How can I make a better product or service for people? Just to wrap up on cognitive biases, we have so many cognitive biases as humans. There's about a hundred. I think there's a whole list on Wikipedia. I wrote about it. We write about it in the book EXO2. At the end of the day, an AI will help you if you want to navigate those cognitive biases. Another going back to the fundamentals of why AI and algorithms are so critical. We're living in a world of an explosion of data. We're seeing the amount of data double every two years and an explosion in sensors. We're hinting towards a trillion sensor economy, I call it, where autonomous cars with LIDAR and radar and cameras and drones flying and augmented reality glasses and everything is just generating massive amount of data. You're heading towards a world where you can know anything you want, anytime you want, anywhere you want. The data is there, but no way to access it. Without AI and algorithms, it becomes a critical filtering point.

I mean, every exo will have to be using AI. And what's magical, I think about the LLMs and generative AI that's emerged is we can use it everywhere, right? One of our team members said, hey, optimize my email subject lines on our newsletter to increase our open rates. And our open rates went up 25% just from that. So we'll start using it everywhere across every business function, accounting, fulfillment, sales, marketing, the whole lot.

So when you talk about the importance of AI, let me just read a couple of quotes here. Sundar Pichai, the CEO of Alphabet, has a quote that I love. He goes, artificial intelligence could have more profound implications for humanity than electricity or fire. I love that quote. And Elon has one which is a little more punchy. He goes, companies have to race to build AI or they'll be made uncompetitive. Essentially, if your competitor is racing to build AI, they will crush you. I put it differently, and I said, but still really black and white, which is there are going to be two kinds of companies at the end of this decade. Those that are fully utilizing AI and those are out of business. And I think it's that black and white. Yeah, I really, truly do.

It completely is. Can I show you an image?

Yeah, please.

Okay, check this out. So we incorporated an AI generative AI chatbot into the book, where you can ask it a question and it will literally look up the entire corpus of the book, pose it with your thing, and then come back with an answer. I've asked it the question here. How do I turn a Brazilian shipping company into an exo? And here's the answer.

Right.

It literally tells you, identify transformative purpose. There's your mtp. Right. It has to align the purpose with the transformational shift in company, leverage external resources. Like, you can benefit from collaborating with other organizations in a bunch of ways. Consider an autonomous unit. You create a separate autonomous unit to develop new disruptive business models and then build a culture of experimentation. Right. And this is pretty damn good. That's like 50k worth of consulting right there. My entire community of 24,000 consultants, Exo People, is going, hey, wait a minute. What did you just do? I think this is so funny.

Digitize them.

Well, as you often say, Right. The crowd is a proxy for AI.

Yeah.

Just like an Uber driver is a proxy for an autonomous car.

Yeah.

So over time, we're going to automate more and more of these tasks. I think there's this unbelievable thing that's happened that nobody expected that we thought we'd automate manual tasks, washing dishes, and we just couldn't figure out how to do that. And what we've automated is all the white collar tasks.

So let me show one image here as well. And it's, you know, something that we've talked about a lot. Here we go. And when will AI reach and or exceed human level AI? So Ray Kurzweil has, for the last 20 years, consistently predicted 20, 29. I mean, the guy is, is, like, committed to that date and everybody in the AI industry was laughing at him. And. But eventually, and it's been polled by all the AI experts, it's gone, like, from 100 years ago to 50 years ago to, you know, 50 years.

They all come closer to Ray.

They all come closer and closer. Then recently, Elon put this one out. He said, AI will be vastly smarter than any human and would overTake us by 2025. Pretty extraordinary. Now, he since tweeted that he said, I think Ray is right about the timing. Maybe it's somewhere between 25 and 29. But for those listening, here's the question. There's no question that we're heading towards. Put aside whether this is AGI or conscious. It's a matter of will this be able to be as good or better than humans in your company? It's coming. And so how are you going to start thinking about this if you're the owner of a business, if you're an investor, if you're an entrepreneur running a company? One of the things I talk about critical to this is every company needs to create or identify, hire, bring in what I call a chief AI officer. So that's one tidbit I want to offer out. What is a chief AI officer? It is not someone coding your own large language model. It is not someone who is really coding. It's more someone who understands what's going on. They understand it at a core and they know the players and they are helping you as the entrepreneur, the CEO, the business owner, the investor, understands the platforms and what to utilize because it's moving so fast that you need that person inside your organization. So one piece of advice, get a.

Chief AI officer in the book we write that by the time you read this chapter, it'll be out of date.

It's such a pain in the ass to write a book these days because.

We had to rewrite big chunks of the book after ChatGPT came out. It's like we're shaking our fist at the gods around this. I want to go on a little bit of a rant.

Okay, let's do that.

The 2029 number, which is called the technological singularity often, which is Ray talks.

To us about the singularity as 2045 versus 2029.

Either way, I hate the discussion. And I'll explain why. One, we don't know what intelligence is. Right now we have about a dozen facets of intelligence, and we measure two pieces of it, which is the speed of thought processing and the ability to match concepts across frameworks. That's how we currently think. But we have emotional intelligence, we have spatial intelligence, we have the eastern concept of presence or awareness. We don't touch on any of that. So what do we mean by intelligence is one big hairy problem of a question. And the second, which touches on the ChatGPT stuff, is what would you constitute overtaking? The minute I can prescriptively describe a task an AI or robot is going to do much better than me anyway. I find it's a great framing discussion, but I don't find it that useful. I think, as you said before, it's how will you use AI? Just like in chess, we all use AI now in chess to help us navigate and do the bog standard openings. And then it comes down to the chess, the AI plus a human being that always turns out to be the best competitor. I think that's where the world would end up.

I mean, there's a lot of dystopian conversation going on right now around AI, and let's dive into that because I really want to take it head on. So there are two conversations. One is will AI take your job? The second conversation is, will AI destroy humanity and become. Both of them are just igniting our amygdalas. It's like boom, boom, boom. Right. And I don't think the global news has really taken on yet, but they'll have a heyday. We're gonna see a.

Why don't you tackle the consciousness one and I'll tackle the jobs one.

All right, well, listen, first of all, I was reading a book called A Thousand Brains by Jeff Hawkins, and it talks about how the brain works and this idea of these cortical columns and three dimensional spacing as the means by which. And I think it's clear to a lot of people who've studied this that currently AI as it's being built is orders of magnitude. It could be millions, if not billions of times less complicated. In other words, it has a long way to go to get to the level of complexity of the human brain. And so I'm not worried about AI becoming conscious anytime soon. The place I get concerned is nefarious actors, terrorists, individuals who are unfortunately looking to do more harm than good using AI to do that. And it's going to be, as always, a virus antivirus competition in that world. And so that's my near term concern. And how do we do that? Right, so we've seen intel, for example, come up with a set of algorithms to determine deep fakes at 99.5% accuracy recently. So we're going to have problems and we're going to solve them. And I can say the world's biggest problems are the world's biggest business opportunities.

The presidential candidate in the Turkey presidential election just resigned because of a sex porn tape. That surface that he claims is a deep fake. I know, it's just, it's just crazy how pervasive.

Wait till the US elections in 2024.

It'S going to be.

I mean, you know, we have, we have all of these, these technologies that are being able to clone your voice and you're going to get a call from your mom asking you, you know, passionately, please son, go vote for this candidate.

It's crazy. So I have a different take on the consciousness thing. We have the same problem. We have no idea what consciousness is. We don't know how to define it, we don't know how to test it. When I think about AI, and I've heard you make this point, you look at PageRank, it's evolving its own intelligence, scanning billions of web pages at the same time. It's a completely complementary type of intelligence to human intelligence. It's not replicative. The Hollywood side will always portray it as a dystopian matrix. Terminator, Skynet. If we're lucky, the robot overlords come and treat us like pets. And if we're unlucky, we're food.

Right?

Like that's pretty much that range that occurs. But in reality we're adding capability to human intelligence, not subtracting or replicating in any way that I've seen. I want to go on a rant about the jobs thing, right, because we've worried. So we did some research on this. The first article that came out saying that robots are going to take all the jobs in five years appeared in 1964. And we have the clipping thing and every five years you see that, you see the same kind of basic article.

So can we go back to that 1964, I don't think it was robots. I think it was automation was going to steal our jobs.

Yeah, but this is a key point. Now let's look at some data. If you look at say Germany or Sweden or Korea, the most automated robotics enabled manufacturing countries in the world, employment has not dropped at all. In cafec, it's increase. They have the lowest unemployment because when you automate the robot work, there's so much more work to be done in problem solving, increased efficiency, better design, etc. My favorite example at a macro level is in the 70s when we created ATM bank machines, there was all this hang wringing going, what will we do with millions of bank tellers that will be out of a job and huge consternation. Should we do this? Big ethical questions and should we not create the machines or not? And what actually happened was the cost of running a branch dropped by 10x and the branches, the banks created 10 times more branches and the number of bank tellers hasn't changed at all. So it turns out when we automate, we increase capacity, we don't drop employment. And this is, we've seen this now time and time and time again in every domain that we've been able to study this. So the likelihood is that if you can do 10 times more as a programmer, it doesn't mean you need 10x less programmers, we just program 10 times more.

Well, it's important listen to folks hearing this and disagreeing. We're going back to our cognitive biases. We have this negativity bias and we just will tend to focus on the dystopian future because that's what we evolved to focus on. And you have to ask yourself the question. The jobs that are being digitized and dematerialized and automated, at the end of the day, a lot of those jobs are going to be dull, dangerous and dirty. And a lot of people, you know, we're going to have robots that are going to clean, you know, homes or hotels and that's great. I don't think that a lot of the people cleaning, doing the cleaning services, that was their dream as a kid, to grow up and do that. So how do we allow automation, AI and robotics and they're both coming together, these are going to be AI driven robots and we see a whole generation of humanoid robots coming. Different conversation. How do we allow the jobs that are not inspiring to be done by them and how do we allow individuals to gain access to the amazing technologies and actually dream a bigger dream? I think, you know, how do you feel about ubi? Are we going to have universal basic income? Salim I think we are.

I'm a huge proponent of it. You know, I remember about several years ago we ran a workshop at Singularity with Tony Robbins there and others. And we kind of looked deep into UBI and we looked at 14 major experiments and where it was implemented fully, the results were outstanding. The challenge is when you use ubi, you can actually reduce government, the need for government by a huge factor. And governments don't like making themselves redundant. And so you've got a cognitive bias in government. Wanting to look at this. I'd like to get back to the exo and AI conversation though. Right. So if you go back to your the comment that we started where you can create a billion dollar startup with three people, this is absolutely possible. Right. So the CEO would be involved in vision and strategy and lead public facing marketing. You have a product lead that will work with AI agents to kind of refine the product, work with the community to develop and define to drop and an operations leader who will basically manage those functions and track the AI bots as they do for their various things. That's pretty much all you need with a whole set of AI bots that will do pretty much everything else. And I think this is going to be prototypical of the future. One thing we write about in the book is that there's probably 10,000 startups that are being built on that premise right now. Right. So many of them will fail, but it doesn't take that many to succeed to completely disrupt the existing industries that we live in.

I think that's a really important point. If you're a large corporation trying to bring AI in and seeing how hard it is and saying, well, I'm not going to get disrupted by this. The challenge is the disruptor is not your normal competition. It isn't the large corporation down the street or the large corporation on the side of the world. It's literally two guys or gals in a garage using these generative AI tools and trying a crazy idea that you would never experiment with because it was too dangerous and coming up with something. It's why Google purchased YouTube when they had Google videos going. It's why Facebook and even look at this, Microsoft buys effectively OpenAI. Microsoft didn't develop all of these generative AI tools. The team at OpenAI did with 130 people. So small teams can do amazing things.

So let me do a live thought experiment.

Sure.

Okay. We have a friend, Will Henshaw, who runs a startup called Focus at Will, which is streaming music to put your brain in a focused alpha. Right. So now it's like a Pandora type service. You sign into it. I wrote the whole first edition of the book listening to this music and put your brain in an alpha focus state. Now I can imagine if you rebuilt that company with AI, you would have the AI compose chunks of music. Okay. Played out randomly using a Mechanical Turk type thing to a million people and said okay, watch where their eyes go or whatever feedback loop to see if their brains go into a passive state and boom. If that operates, that way, then that piece of music generates an active state. And now you do product development for free.

Rapid experimentation. Right.

You can run a collection. Then you have a system that's out there optimizing for sales and running the funnel saying how many people switch from free to freemium to what and what prompts can you bring to bring them back in and encourage them to sign up? Longer terms, you could vary the terms by what some people might like or not like. And the all the accounting and collection side is handled already. So you can essentially run that entire company pretty much autonomously going forward. And I think that's what's going to happen more and more going forward. It's just going to be thousands and thousands and thousands of companies being built on a totally new premise. And it's going to be the 20 year olds that do it because they have no biases from before.

I totally agree. And the marginal cost of starting a business is approaching zero. You know, we had a, when you and I were running our workshops at Singularity University a decade ago, and then five years ago we were showing these charts that said a decade ago it cost this much money to start a company.

Several million dollars.

Yeah. You had to buy the servers, you had to buy the employees, you had to buy the software, you had to buy the bandwidth to get the stuff out there. And then it was going from $5 million to $500,000 to $50,000 to $5,000 to 500. And now I mean the marginal cost using generative AI. I have a summer intern out of Cornell's computer science team and it's like he's getting his master's degree. And I said, are you working on any startups? He goes, yeah, I've got three generative AI startups I'm working on right now. Like, oh my God, it's like not one, three and multiply that. And I run a venture fund, Bold Capital, and we're just seeing a massive influx of generative AI companies now. I don't know, I could imagine there's a million startups going on right now and 99.99% could fail. But if you have 100 breakthrough companies that come out of no place, the question is, how do you tell the difference between the Cambrian garbage and the Cambrian Explosion gold?

Well, the beauty of it is that I used to think of startups as turtle eggs. A turtle will lay 100 eggs and you've got 100 little turtles running towards the beach and the birds are eating them, the animals are them. Then they get to the water and the fish are eating them and the surface pounding on them. And only five of the original hundred turtles will actually get to the bottom, right? And the problem if you're an investor is which five? Because there's so many chaotic conditions along the way. But now, forget 100 turtles. You can launch a million turtles, right? And some of them are going to go nuts. And I think the creative application of ChatGPT and other tools and other, in various domains, creative writing, etc, etc, totally gonna. Totally gonna take over the world. Can I show you my favorite ChatGPT prompt?

Yeah, please. Okay.

I'm here.

I'm here to learn.

So what I did was I said rewrite the Bible, Genesis chapter as a rap song.

Okay.

And look at this.

You're gonna have. You're gonna have to sing it for me.

So it says, let's flip it back to the Genesis. When the world was dark void in a deep abyss God stepped up to the plate no time to reminisce Spoke the words let the relight yeah, he insisted in the beginning yo. The earth was formless But God had a plan his vision enormous Divided the light from the dark so flawless called light day the dark night he was dauntless and it just goes on like that. It's amazing. It's absolutely amazing that you can do this right in this Shakespearean.

And it goes on and on and on.

It just goes on and on and on.

I hope you go on camera and sing this and publish it.

We'll let one of our sons do that. They're more.

Honestly, it's like, do you start to wonder if every rap song and every book and every blog is written by generative AI?

It's going to be very shortly. And this brings up some really, really big questions that are, I think, outside the scope of this discussion and to how do we deal with the infinite creativity? We now have an abundance of creativity. It used to be scarce, and now we have abundance.

Hey, everybody, this is Peter. A quick break from the episode. I'm a firm believer that science and technology and how entrepreneurs can change the world is the only real news out there worth consuming. I don't watch the Crisis News Network. I call CNN or Fox and hear every devastating piece of news on the planet. I spend my time training my neural net the way I see the world by looking at the incredible breakthroughs in science and technology, how entrepreneurs are solving the world's grand challenges, what the breakthroughs are in longevity, how exponential technologies are transforming our world. So twice a week, I put out A blog. One blog is looking at the future of longevity, age reversal, biotech, increasing your health span. The other blog looks at exponential technologies, AI, 3D printing, synthetic biology, AR, VR, blockchain. These technologies are transforming what you as an entrepreneur can do. If this is the kind of news you want to learn about and shape your neural nets with, go to dmanandis.comblog and learn more. Now back to the episode. Yeah, one of my favorite examples of someone using generative AI in a really blow my mind mindset was this individual. This woman on one of my implementation workshops for A360 said, I'm using. I was saying, going around the room saying, what are you using generative AI for? And this person said, I'm using generative AI to make patents understandable. Because if you've ever read a patent, they're in this obscure language. And so you put in a patent. Amazing, huh? Amazing. You put in a patent number, just the patent number, and say, what does this patent mean in plain English in 100 words, right? And you get an answer. Now the thing that she did, which was amazing is get this. She said, okay, this is my company, this is what we do. And here are two patents. How would we use these two patents together to transform our company? Holy shit. Amazing. And she got some blow your mind ideas. It's like what AI is doing so well is. It's interpolating and extrapolating.

Yeah.

I mean, it's still blowing your mind, right?

Yeah, my mind's blown because now I'm thinking, wow, you take a company like IBM that has a huge patent portfolio and you say to IBM, let's build an incubator on top of that patent portfolio with generative. You won't do it yourselves because you're IBM, but let's help you build that and let's see where it goes. That's incredible. That's amazing potential. So, you know, there's all sorts of aspects of this that go forward. I think it's absolutely critical if you're building a startup of any kind or running a company to get everybody access to generative AI, first of all. The second thing to do is to start playing with different models, asking it exactly that, here's my ip, what can I do with it?

Can I make a quick add on there?

Go.

If you're in a meeting, if you're in your board meeting, if you're in a management meeting, have OpenAI or Bard or whatever you want to use open on the screen alongside and be asking it for its ideas in Every conversation you're having, and I guarantee you it will transform the speed of your conversations. It becomes a thought partner in everything you're doing.

We should have had it as part of this podcast. Kring, how could we make this discussion a little richer?

Well, actually, I mean, all the questions I'm asking are just coming from ChatGPT, not me. But in all honesty, it's incredibly. It is your partner. There's a great meme going on right now, and it's in the loss of jobs. AI is not going to take your job. It's someone using AI that's going to take your job. And I agree with that. I think everybody is going to need to have their co pilot. I was having a dinner with Reid Hoffman, I don't know, a couple months ago, and we're talking about copilots. The idea that every profession is going to have an AI copilot. Whether you're a lawyer, a doctor, an artist, a writer. You're going to have your version of Jarvis that is there with you, knows you, and is making you just not even 10 times more productive, 100 times more productive. It's amazing. I don't want to drag this on too long, but I want to come back to AI and algorithms. It's one of your external attributes of an exponential organization. Let's bring it back as advice to the entrepreneur. Once again, I'll start with one and then hand it over to you.

Sure.

Here's a big idea. There is a billion dollar question that if you knew the answer to that billion dollar question, it would transform your company. And I think if you know what you're looking for, if you know, it's like I'm looking for, here's an example. I'm looking for the lowest price real estate in the most expensive neighborhood where the house is on sale because the person passed away and has no children. It's like, you know, if that is what you want to know, you can find that data. The data is out there and an AI can scrape it and go and gather it and give you those target homes to go purchase. So what is that billion dollar question? Because we're heading towards a world where you can know anything you want, anytime you want, anywhere you want, where there's a massive amount of data and AI will parse that for you. But you have to be clear. Like I talk about what I want for my kids. I want them to have a purpose. I also want them to learn how to ask great questions.

Absolutely. So I take it a step further and I Would say, take your MTP, go to a ChatGPT, generative AI stability, whatever equivalent, and say, what intellectual property or techniques or technologies can I build to build a billion dollar company implementing my mtp and start that prompt. Because if you start with the mtp, you've got the problem space nicely laid out and let it find the spaces, the white spaces in that domain that need to be solved. You know your tool for MTP plus moonshots, now you add AI to it and say, okay, how do I accomplish this moonshot?

Yeah, in fact, we built that. There's a Peterbot version. A friend of mine, my chief AI officer, which is, by the way, the third piece of advice. Bring in a chief AI officer. If that's you as an entrepreneur, fantastic. If you're, if that's not you, if that's not your area of expertise and doesn't need to be, bring in someone who is your strategic thinker in this arena. So Steve Brown is my strategic thinker in this arena and he built a Peterbot. And so we did this experiment where we started with an MTP, you can go to dashmandis.com MTP and it will help you design your MTP. And then with the MTP, you can go to Moonshot and develop your moonshot. And then said, break this moonshot down into 10 steps that I can execute it and give me ideas on what to do. And then he said, write me a proposal to the Gates foundation to implement the first step of this. And it did. And it wrote this incredible proposal and letter to the Gates Foundation. And so this is about the speed of action, faster, never staring at a blank page.

If you can develop your MTP and then run a process like that to make it to action it, you now have moved nine steps forward in building out your venture, your nonprofit, your business, whatever, and you're well on your way. So I think the potential for this is incredible. If you're an existing company, AI and algorithms becomes absolutely mandatory to start thinking about implementing it, get a chief AI officer. And you have to do that now. Do not wait even a week before you start applying this.

The other piece of advice I would give is what is the unique data that you have or that you can collect? Right. We're going to see large language models, generative AI, AI in general, sort of starting to demonetize businesses. And there was an article that came out recently that said it was a leaked memo out of Google. It said there's no moat, no protective surrounding around generative AI models because of the Rapid rise of open AI systems like Stability AI and others. But what makes you unique is the data you own. And so as a company going out and. And creating a unique data set or identifying your unique data set and then applying AI to that unique data set gives you value.

Yeah. In fact, we now know of companies that have taken figure out how to collateralize all their data and AI into a separate entity and they're able to up their market cap by like 4 or 5x just by taking the data and collateralizing into a separate structure. So it's amazing. Possible today.

Yeah. I was at a event that Deloitte was running for chief financial officers like three years ago and like 500 of them, you know, anyway, I can go. It was a speaking gig for me and I asked the question, how many of you have put data on your balance sheet as an asset? And none of them raised their hands. And I'm like, that's insane.

This is a very new thing. We've actually partnered with somebody that knows how to do this. So it's huge. It's going to kind of. I think that'll be the predominant. That whole idea of data is the new oil suddenly becomes to fruition. But I think the point you made earlier needs to be reemphasized. If you have access to a rich seam of data. Right. There's some incredible businesses you could build on top of that or approach a company that has existing data, a nursing home, Zillow, which has unbelievable data on real estate, and start building businesses on top of that. It's incredible what's going to be possible.

Any last advice for people thinking about this external attribute for their.

I think it's just. Just get started as fast as you can because this is one of those where you cannot afford to be left behind on this paradigm. You have to learn. It has to become a key core competency inside your organization. Like yesterday.

Yeah. Two kinds of companies by the end of this decade.

There you go.

Yeah.

All right.

All right, buddy. See you soon enough. Yeah. Take care.